Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The readOnlyHint annotation already establishes this is a safe read, but the description adds substantial value beyond it: the agent learns the response contains a workflow, a brief, at most 3 questions each carrying a default, and forbidden silent pattern choices. Crucially it discloses that results are partially gated — free content versus Pro rules named only by title — which warns the agent its output will be incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences with the imperative timing constraint first, followed by the return description and the free/Pro caveat. Every clause carries information; the parenthetical examples are useful rather than padding. Slightly dense, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must convey what returns, and it does at a useful level of abstraction: workflow, brief, questions with defaults, rule list. Combined with the paywall caveat and the readOnly annotation, an agent has enough to call this correctly and interpret partial results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter is fully documented in the schema (100% coverage), establishing a baseline of 3-4. The description still adds meaning by explaining the effect of supplying it: passing the task causes rules most likely to matter to be listed, framing the parameter's purpose rather than just its format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete verb and resource — call this before designing or building a user interface — and enumerates the scope (a page, screen, component or flow). It also states what comes back (the ihumane workflow and the brief), so an agent can distinguish it from the code/copy/product variants in the sibling set without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The timing is explicit and front-loaded: call this BEFORE designing or building any UI. It further clarifies conditional usage — 'if you pass the task' — which tells the agent when populating the optional parameter pays off. It stops short of naming an alternative tool or stating exclusions, so this is clear context without routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.